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In this study, we consider a quantum channel that may help to discriminate quantum states, by which we may provide the solution for the unsolved problem of discrimination of quantum states. For the quantum channel to help the problem of discriminating given quantum states, the quantum channel should not change the guessing probability as well as the optimal measurement in minimum error discrimination of those quantum states. Therefore, we investigate a quantum channel that preserves an optimal measurement and the guessing probability with minimum error discrimination of quantum states. Then, we show that the channel does not exist in every set of quantum states but does exist when the channel and an optimal measurement commute with each other. The effectiveness of the channel can be shown more explicitly when the discrimination of linearly independent quantum states, which has not been solved yet, is considered. When we apply the channel to linearly independent quantum states, the discrimination of quantum states can be transformed into a problem in which the number of quantum states in discrimination is reduced, and we can provide a means of obtaining an answer to an unsolved quantum state discrimination. As an unsolved problem of discrimination of quantum states, we consider an ensemble of three pure states with real coefficients, whose subsets contain Unitary symmetry-called partial symmetry. By applying our strategy, we can provide an analytic result for optimal discrimination to the ensemble of three pure states with partial symmetry. [ABSTRACT FROM AUTHOR]

Real-time monitoring of suspended particulate matter (PM) has become essential in daily life due to the adverse effects of long-term exposure to PMs on human health and ecosystems. However, conventional techniques for measuring micro-scale particulates commonly require expensive instruments. In this study, a smartphone-based device is developed for real-time monitoring of suspended PMs by integrating a smartphone-based digital holographic microscopy (S-DHM) and deep learning algorithms. The proposed S-DHM-based PM monitoring device is composed of affordable commercial optical components and a smartphone. Overall procedures including digital image processing, deep learning training, and correction process are optimized to minimize the prediction error and computational cost. The proposed device can rapidly measure the mass concentrations of coarse and fine PMs from holographic speckle patterns of suspended polydisperse PMs in water with measurement errors of 22.8 ± 18.1% and 13.5 ± 9.8%, respectively. With further advances in data acquisition and deep learning training, this study would contribute to the development of hand-held devices for monitoring polydisperse non-spherical pollutants suspended in various media. [ABSTRACT FROM AUTHOR]

The Pacific Island countries have a substantial socio-economic dependency on fisheries. Skipjack tuna is one of the most important species in the Western Central Pacific (WCP) and its catches in this region exhibit a spatio-temporal variability influenced by ocean conditions, mainly the El Niño-Southern Oscillation (ENSO). This study investigates the relationship between skipjack tuna catch amounts and environmental variables in the equatorial Pacific during 1990–2014, and evaluates the potential predictability of the catches based on their statistical relationship. A series of regressed and reconstructed spatial patterns of upper-ocean temperature, salinity, currents and precipitation represent ENSO-like variability, and their principal component time series are used to estimate the predictability of skipjack tuna catches in the Federated States of Micronesia (FSM). ENSO-like variability depicted from 100 m temperature and 5 m salinity in the equatorial Pacific exhibit a significant predictability for the annual catch amount in the FSM for several years with a training period of > 20 years. This suggests that the subsurface temperature or near surface salinity can be a better predictor of ecosystem variability than widely used sea surface temperature. Applications of this result to other species could have broad implications for the fishery industry in the WCP. [ABSTRACT FROM AUTHOR]

This paper proposes a DC motor current control algorithm using a proportional-integral linear quadratic tracking (LQT) controller with a disturbance observer for the electronic stability control (ESC) brake system. Previously researched algorithms related to current control using disturbance rejection are robust control, adaptive control, LQT, or proportional-integral disturbance observer (PI-DOB); each of them has both advantages and disadvantages. The proposed algorithm uses a disturbance observer in order to improve disturbance rejection performance while avoiding the drawbacks of high gain property. Additionally, the proposed algorithm adds integral control in order to improve performance in the low frequency bands. In order to assess the performance of the proposed algorithm, simulations and experiments are performed in the time and frequency domains to compare the proposed algorithm with different algorithms which are actually implemented into the ESC. The proposed algorithm shows good characteristics near the cut-off frequency, which can be confirmed clearly by the time domain results. [ABSTRACT FROM AUTHOR]

In this study, we present the first actual working system that can project content onto a tunnel wall from a moving subway train so that passengers can enjoy the display of digital content through a train window. Our stand-alone system can be easily deployed to existing trains because it does not assume any specific type of interface requiring data transfer with the train. To effectively estimate the position of the train in a tunnel, we propose counting sleepers, which are installed at regular interval along the railway, using a distance sensor. In the preprocessing step, the side depth variation along the tunnel is stored in synchronization with the train location in a tunnel profile. The tunnel profile is constructed using pointclouds captured by a depth camera installed next to the projector. The tunnel profile is used to identify projectable sections that will not contain too much interference by possible occluders. The tunnel profile is also used to retrieve the depth at a specific location so that a properly warped content can be projected for viewing by passengers through the window when the train is moving at runtime. Here, we show that the proposed system can operate on an actual train and evaluate the quality of the projection results through simulation. [ABSTRACT FROM AUTHOR]